There are various ones of utilization as apparatuses for color-image processing, including scanners, digital cameras, printers and displays. As a method to exchange image data between such apparatuses, there is transformation into color-image data wherein the color image data inputted at an input unit is once transformed into a color space not relying upon the apparatus and then outputted to an output unit. Such a system is called a color management system.
In the color management system, by establishing transformation between the signal of the image input unit and the color space not relying upon the apparatus, data can be delivered to any of the image output units. There is no need to determine color transforming processes in the number of combinations of input and output units. Meanwhile, in case the color image data inputted at the image input unit is previously transformed into a device independent color space not relying upon illumination besides upon the apparatus, it is possible to output from the output unit an image of under an illumination different from the illumination of during image input. The device independent color space not relying upon the apparatus is generally an XYZ tri-stimulus value prescribed by the International Standard Organization CIE or an L*a*b* equivalent color space.
By nature, color is expressed by a spectral radiance as to in what degree each wavelength of color is contained. The XYZ tri-stimulus value is of three scalar quantities obtainable by weighting the spectral radiance through the color-matching function as defined under the CIE and thereafter integrated in the visible portion. Meanwhile, the L*a*b* equivalent color space is a three-dimensional color space the XYZ tri-stimulus value is normalized by reference white.
Color, in nature, is 31-dimensional huge data sampled at an interval of 10 nm over a visible portion of from 400 nm to 700 nm. On the contrary, the expression form of color in three dimensions, such as XYZ tri-stimulus value or L*a*b* equivalent color space has been so far used, instead of spectral colors, as the quantity representative of a color to be perceived by the human, because of the reason the human eyes are to perceive by three types of cones.
However, by the recent improvement in information processing capability, there is a trend toward developing the apparatuses spectrally expressing colors in place of XYZ tri-stimulus values and L*a*b* equivalent color spaces. Spectral expression includes spectral reflectance, spectral transmittance, spectral radiance, spectral radiant intensity and so on. Spectral radiance contains illuminant information, because it expresses an amount of light radiated from a subject. The spectral radiance, removed of a spectral distribution of illuminant, is termed as spectral reflectance or spectral transmittance.
There is a widespread of the color management systems for handling spectral reflectance or transmittance, of spectral expressions, as a device independent color space. Namely, those are the systems which estimate a spectral reflectance or transmittance of a subject, to handle a spectral reflectance image or spectral transmittance image as an image thereof. Hereinafter, the color in spectral expression as represented by spectral reflectance or transmittance is collectively referred to as a spectral color.
The apparatuses handling spectral colors include, for example, a skin color measuring method and spectral reflection spectrum estimating method described in JP-A-7-174631 and a color simulation apparatus described in JP-A-9-233490. In these apparatus, a spectral reflectance image of a subject is estimated from an image inputted at an image input unit, in order to analyze the physical properties of the subject or simulate an image of the subject as viewed under various illuminants.
Traditionally, color editing has been conducted in the color spaces that depend to the respective apparatus such as cameras, displays, printers and the like, i.e. in the camera RGB color spaces, printer CMYK color spaces, display RGB color spaces. However, by the widespread color management systems dealing with the spectral colors, there arise the applications for color-editing or color-correcting the spectral image as independent color spaces.
The apparatuses for color-editing spectral images include, for example, a color processing apparatus described in JP-A-7-162694. According to this document, the spectral color of color sample is displayed in the form of a graph in a spectral color display window, whereby the user is allowed to directly edit a graph curve to a desired form by the use of an editor, such as “illustrator” by Adobe. Thereupon, the edited spectral color is transformed into an xy chromaticity and an HCV signal which are respectively displayed in an xy chromaticity diagram display windows and an HCV display window. The user again edits the spectral color with reference to the values in the xy chromaticity diagram display windows and HCV display window.
On the other hand, the apparatus for color-correcting spectral images, e.g. the apparatus for estimating a spectral reflectance from an image inputted at the image input unit, includes the foregoing skin color measuring method and spectral reflection spectrum estimating method described in JP-A-7-174631 and color simulation apparatus described in JP-A-9-233490.
These apparatuses carry out pincipal-component analysis of spectral reflectance and express it with basis in m-dimensions lower than 31-dimensions. Then, a coefficient m-dimensional vector is estimated from the input image data by a neural network. Next, a spectral reflectance is computed from the estimated m-dimensional vector, thereby estimating the spectral reflectance.
However, in expressing a spectral reflectance on certain basis, unless the basis contain something like a delta function narrow in wavelength width, such a color cannot be estimated. Namely, this results in an impossibility to obtain, as an estimation value, a quite saturated color having a narrow wavelength width. Consequently, the estimated image is of an image giving an expression comparatively low in saturation. For this reason, there is a desire for an approach to color-correct an estimated spectral image into a more saturated color. However, there exist no systems for making color-correction in the spectral image.
In the conventional spectral-image color-editing apparatus, the human is required to directly modify the shape of spectral-color curves as huge as 31-dimensions. In what degree the color is changed by what way correction is done, is the operation not easy to understand and hence difficult, despite of the capability to utilize guidance including XYZ signals, L*a*b* signals or HCV signals.